Abstract:
Introduction of fake drugs in the pharmaceutical market poses a serious challenge. poses risk to human wellbeing, leading to treatment failures, antimicrobial resistance, and undermining trustinhealthcare systems. The traditional detection techniques such as manual inspection and laboratory. Testing is slow, expensive and cannot be used widely. These are tackled in this project. Restrictions by coming up with a system, named MediAuth, which is an end-to-end system that integrates Deep.Automated learning, Optical Character Recognition (OCR), and Blockchain technology. Traceability and authentication of medicine. The architecture of the system is a tri-portal system with an Admin Portal where medicines are registered. And retraining models, a User Portal with real-time verification, and Portal Portal with a Blockchain. Certificate transparency. A strong database of genuine and fraudulent medicine pictures was obtained. Trained a MobileNetV2 deep learning model, which had 95.8 percent visual accuracy. Authentication. Tesseract OCR is used to extract batch numbers automatically. And metadata, a permissioned Hyperledger Fabric blockchain is an immutable one. Authentication and provenience of individual medicine registered.
